Sketch-Based 3D Model Retrieval using Diffusion Tensor Fields of Suggestive Contours

The number of available 3D models in various areas increases steadily. Effective methods to search for those 3D models by content, rather than textual annotations are crucial. For this purpose, we propose a new approach for content based 3D model retrieval by hand-drawn sketch images. This approach to retrieve visually similar mesh models from a large database consists of three major steps: (1) suggestive contour renderings from different viewpoints to compare against the user drawn sketches; (2) descriptor computation by analyzing diffusion tensor fields of suggestive contour images, or the query sketch respectively; (3) similarity measurement to retrieve the models and the most probable view-point from which a model was sketched. Our proposed sketch based 3D model retrieval system is very robust against variations of shape, pose or partial occlusion of the user drawn sketches. Experimental results are presented and indicate the effectiveness of our approach for sketch-based 3D model retrieval